Minimum effort factor approach for sensor-based control of a four-joint 6-dof redundant manipulator

A sensor-driven control model and a minimum effort control algorithm in terms of time and energy expended during the execution of a movement strategy are described and validated for a multijointed cooperating robotic manipulator. Considering smooth, human-like (anthropomorphic) movements, using joint motion profiles achievable in real time as well as sensory information from all joints, and evaluating the total work expended by each manipulator joint during the execution of a movement strategy, a minimum effort motion trajectory is synthesized to precisely and efficiently position the robotic arm end-effector. This sensor-based approach significantly reduces the computational requirements for such cooperative motion. The minimum effort control algorithm generates several human-like arm movement strategies and selects the best strategy on the basis of expendable effort. The algorithm has an inherent basis to deal with obstacles in an efficient way. Detailed examples are described from the simulation studies. © 1994 John Wiley & Sons, Inc.     

Towards nonadaptive and adaptive control of manipulation robots

Control synthesis for robotic systems with a variable payload is considered. First, we synthesize a robust, nonadaptive decentralized control using an approximative system model. Then, we analyze the stability of an exact system model. We thus check whether the robotic manipulator is stabilized for all allowable payload variations. If the simple decentralized control cannot accommodate all expected payload variations we introduce additional load, nonadaptive, feedback loop. This global control requires force transducers to be implemented in manipulator joints. If such nonadaptive control cannot stabilize robotic manipulator trajectories we suggest another adaptive control scheme. This control scheme includes an algorithm for on-line identification of variable payload and adaptation of local gains.     

Identification of Contact Dynamics Parameters for Stiff Robotic Payloads

This paper investigates and demonstrates the feasibility of identifying contact dynamics parameters for stiff robotic payloads using a robotic system. The contact dynamics model for stiff payloads is motivated, and theoretical parameter values and bounds are provided. Then, the effect of nonidealities such as surface roughness and plastic deformation on the theoretical values is demonstrated. A row-wise-scaled total least-squares parameter estimation algorithm is proposed and applied to experimental data measured using the special purpose dexterous manipulator task verification facility manipulator at the Canadian Space Agency. The experimental results are compared to a separate set of experiments with a material testing machine as well as finite-element modeling results. Finally, the experimental findings are generalized by providing guidelines for the maximum identifiable payload stiffness as a function of the position resolution, the maximum exertable force, and the structural stiffness of the robotic system.     

Motion trajectory of human arms based on the dual quaternion with motion tracker

In this paper, we present an algorithm for human motion capture of the real-time motion trajectory of human arms based on wireless inertial 3D motion trackers. It aims to improve the accuracy of inertial motion captures and quickly reconstruct some human movements. To evaluate the performance of the proposed dual quaternion algorithm, we present the prototype design. The wireless inertial measurement system and Kinect device are introduced simultaneously in capturing human motion. The dual quaternion algorithm incorporates features of the quaternion rotation and translation. So the singular points of Euler angles can be avoided. Dual quaternion algorithm and DCM(direction cosine matrix) are used to reconstruct human arm movements respectively. Compared with the computing speed in Matlab, the speed of the dual quaternion is faster than it of DCM. To the end, we propose a 3D ADAMS human robotic model for simulating the motion trajectory using dual quaternion algorithm. The results show that the dual quaternion can achieve capabilities of a positive DCM solving, which completed between body segments rotating and translating the coordinate system transformation. Also it can effectively drive in real-time a human model to animate movement, and provide a good algorithm.     

A review on model reference adaptive control of robotic manipulators

The accuracy of the motion control for robotic mechanisms will have an effect on their overall performance. Under the condition where the robotic end-effector carries different loads, the motions for each joint of robotic mechanisms change depending on different payload masses. Conventional control systems possess the potential issue that they cannot compensate the load variation effect. Adaptive control, especially the model reference adaptive control (MRAC), has therefore been put forward to handle the above issue. Adaptive control is generally divided into three categories, model reference, self-tuning and gain-scheduled. In this study, the authors only focus on the model-reference approach. To the best of the authors’ knowledge, very few recent research articles can be found in the area of MRAC especially for robotic mechanisms since robotic system is a highly nonlinear system, and it is difficult to guarantee the stability of MRAC in such system. This study presents a review and discussion on the MRAC of robotic mechanisms and some issues of MRAC for robotic mechanisms are also demonstrated. This study can provide a guideline for upcoming research in the field of MRAC for robotic mechanisms.     

Robustness of decentralized robot controller to payload variation

The decentralized controller for manipulation robot is tested for its robustness to payload variation. First the local controllers are synthesized to withstand variation of inertia round the joints and then the global stability of the robotic system is examined. Three various situations are discussed: a) when actuator inertia is large in comparison to mechanism inertia, b) if the variation of payload is small in comparison to mechanism inertia, and c) if the large variation of payload parameters are expected. An algorithm for testing the robustness of the robot control to parameter variation is established, too. The purpose of the algorithm is to determine the allowable variation of the payload parameters which can be withstood by the simple decentralized controller. On the other hand, by this algorithm the local servosystems can be synthesized which are capable to withstand assumed parameter variation. This synthesis is demonstrated on an example of particular robotic system.     

Vision-Based Robotic Motion Control for Non-autonomous Environment

A visual servo control system with SOPC structure is implemented on a retrofitted Mitsubishi Movemaster RV-M2 robotic system. The hardware circuit has the functions of quadrature encoder decoding, limit switch detecting, pulse width modulation (PWM) generating and CMOS image signal capturing. The software embedded in Nios II micro processor has the functions of using UART to communicate with PC, robotic inverse kinematics calculation, robotic motion control schemes, digital image processing and gobang game AI algorithms. The digital hardware circuits are designed by using Verilog language, and programs in Nios II micro processor are coded with C language. An Altera Statrix II EP2S60F672C5Es FPGA chip is adopted as the main CPU of the development board. A CMOS color image sensor with 356 ×292 pixels resolution is selected to catch the environment time-varying change for robotic vision-based servo control. The system performance is evaluated by experimental tests. A gobang game is planned to reveal the visual servo robotic motion control objective in non-autonomous environment. Here, a model-free intelligent self-organizing fuzzy control strategy is employed to design the robotic joint controller. A vision based trajectory planning algorithm is designed to calculate the desired angular positions or trajectory on-line of each robotic joint. The experimental results show that this visual servo control robot has reliable control actions.     

Robust Adaptive Control of Cooperating Mobile Manipulators With Relative Motion

In this paper, coupled dynamics are presented for two cooperating mobile robotic manipulators manipulating an object with relative motion in the presence of uncertainties and external disturbances. Centralized robust adaptive controls are introduced to guarantee the motion, and force trajectories of the constrained object converge to the desired manifolds with prescribed performance. The stability of the closed-loop system and the boundedness of tracking errors are proved using Lyapunov stability synthesis. The tracking of the constraint trajectory/force up to an ultimately bounded error is achieved. The proposed adaptive controls are robust against relative motion disturbances and parametric uncertainties and are validated by simulation studies.     

A PSO-based algorithm designed for a swarm of mobile robots

This paper presents an algorithm called augmented Lagrangian particle swarm optimization with velocity limits (VL-ALPSO). It uses a particle swarm optimization (PSO) based algorithm to optimize the motion planning for swarm mobile robots. Considering problems with engineering constraints and obstacles in the environment, the algorithm combines the method of augmented Lagrangian multipliers and strategies of velocity limits and virtual detectors so as to ensure enforcement of constraints, obstacle avoidance and mutual avoidance. All the strategies together with basic PSO are corresponding to real situations of swarm mobile robots in coordinated movements. This work also builds a swarm motion model based on Euler forward time integration that involves some mechanical properties such as masses, inertias or external forces to the swarm robotic system. Simulations show that the robots moving in the environment display the desired behavior. Each robot has the ability to do target searching, obstacle avoidance, random wonder, acceleration or deceleration and escape entrapment. So, in summary due to the characteristic features of the VL-ALPSO algorithm, after some engineering adaptation, it can work well for the planning of coordinated movements of swarm robotic systems.     

Dynamic Analysis and Control Synthesis of Grasping and Slippage of an Object Manipulated by a Robot

Grasping an object by a cooperating system such as multi-fingered hands and multi-manipulator robotic system has received much attention. Research has focused on analysis of force-closure grasps and the synthesis of optimal grasping, when there is no slipping condition. Although the control system is designed to keep the contact force in the friction cone and avoid the slipping condition, slippage can occur for many reasons. In this research, dynamics analysis and control synthesis of a manipulator moving an object on a horizontal surface using the contact force of an end-effector are performed considering the slipping condition. Equality and inequality equations of frictional contact conditions are replaced by a single second-order differential equation with switching coefficients in order to facilitate the dynamic modeling. Accuracy of this modeling is verified by comparing the results of the model with those of SimMech. Using this modeling of friction, a set of reduced order form is obtained for equations of motion of the system. A new method is proposed to control the object motion and the end-effector undesired slippage based on the reduced form. Finally, performance of the method is evaluated both numerically and experimentally.     

Precise planar motion measurement of a swimming multi-joint robotic fish一种面向多关节机器鱼平面运动的精确测量方法

This paper presents a method for planar motion measurement of a swimming multi-joint robotic fish. The motion of the robotic fish is captured via image sequences and a proposed tracking scheme is employed to continuously detect and track the robotic fish. The tracking scheme initially acquires a rough scope of the robotic fish and thereafter precisely locates it. Historical motion information is utilized to determine the rough scope, which can speed up the tracking process and avoid possible ambient interference. A combination of adaptive bilateral filtering and k-means clustering is then applied to segment out color markers accurately. The pose of the robotic fish is calculated in accordance with the centers of these markers. Further, we address the problem of time synchronization between the on-board motion control system of the robotic fish and the motion measurement system. To the best of our knowledge, this problem has not been tackled in previous research on robotic fish. With information about both the multi-link structure and motion law of the robotic fish, we convert the problem to a nonlinear optimization problem, which we then solve using the particle swarm optimization (PSO) algorithm. Further, smoothing splines are adopted to fit curves of poses versus time, in order to obtain a continuous motion state and alleviate the impact of noise. Velocity is acquired via a temporal derivative operation. The results of experiments conducted verify the efficacy of the proposed method.     

Robust motion control with the consideration algorithm of joint torque saturation for a redundant manipulator

As each joint actuator of a robot manipulator has a limit value of torque, the motion control system should consider the torque saturation. In order to consider the torque saturation in a transient state, this paper proposes a new redundant motion control system using the autonomous consideration algorithm on torque saturation. A Jacobian matrix of a redundant robot manipulator can select the optimal one considering its motion energy in the steady state. When the motion control system carries out fast motion and quick disturbance suppression, a high joint torque is required in a transient state. In the experimental results, under the condition of having a large payload torque and a fast motion reference, the proposed redundant manipulator control realizes the quick robot motion robustly and smoothly.     

Multisensor controlled robot system for recognizing and tracking moving multiple objects

This paper presents a cost-efficient, real-time vision-sensor system for identifying, locating and tracking objects that are unknown and randomly placed on a moving conveyor belt. The visual information obtained from a conventional frame-store unit and an end-effector based proximity sensor outputs are incorporated in a fuzzy-logic control algorithm to make the robotic manipulator grasp moving objects. The robot movements are going to be the result of the comparative measurements made by the sensors after the motion of the moving target is predicted and the gripper is brought into a zone close to the object to be grasped by the application of a vision system. The mobile object is traced by controlling the motion of the end-effector with an end-effector based infrared proximity sensors and conveyor position encoder by keeping the gripper's axis to pass through a median plane of the moving object. With this procedure and using the fuzzy-logic control, the system is adapted to pursue of a mobile object. Laboratory experiments are presented to demonstrate the performance of this system. ©1999 John Wiley & Sons, Inc.     

Development of a biomimetic robotic fish and its control algorithm

This paper is concerned with the design of a robotic fish and its motion control algorithms. A radio-controlled, four-link biomimetic robotic fish is developed using a flexible posterior body and an oscillating foil as a propeller. The swimming speed of the robotic fish is adjusted by modulating joint's oscillating frequency, and its orientation is tuned by different joint's deflections. Since the motion control of a robotic fish involves both hydrodynamics of the fluid environment and dynamics of the robot, it is very difficult to establish a precise mathematical model employing purely analytical methods. Therefore, the fish's motion control task is decomposed into two control systems. The online speed control implements a hybrid control strategy and a proportional-integral-derivative (PID) control algorithm. The orientation control system is based on a fuzzy logic controller. In our experiments, a point-to-point (PTP) control algorithm is implemented and an overhead vision system is adopted to provide real-time visual feedback. The experimental results confirm the effectiveness of the proposed algorithms.     

Design and performance evaluation of a biomimetic microrobot for the father–son underwater intervention robotic system

Underwater intervention is a favorite and difficult task for AUVs. To realize the underwater manipulation for the small size spherical underwater robot SUR-II, a father–son underwater intervention robotic system (FUIRS) is proposed in our group. The FUIRS employs a novel biomimetic microrobot to realize an underwater manipulation task. This paper describes the biomimetic microrobot which is inspired by an octopus. The son robot can realize basic underwater motion, i.e. grasping motion, object detection and swimming motion. To enhance the payload, a novel buoyancy force adjustment method was proposed which can provides 11.8 mN additional buoyancy force to overcome the weight of the object in water. Finally, three underwater manipulation experiments are carried out to verify the performance of the son robot. One is carried by swimming motion and buoyancy adjustment; the other two are only carried by buoyancy adjustment. And the experimental results show that the son robot can realize the underwater manipulation of different shape and size objects successfully. The swimming motion can reduce the time cost of underwater manipulation remarkably.     

Multiple-arm space free-flying robots for manipulating objects with force tracking restrictions

Multiple Impedance Control (MIC) is an algorithm that enforces designated impedance at various levels, i.e. on the manipulated object, all cooperating manipulators, and the moving platform of a robotic system. In this paper, a force tracking strategy inspired by a human control system is added to the MIC algorithm and the general formulation is revised to fulfill a desired force tracking strategy for object manipulation tasks. The stability analysis of the MIC algorithm based on the Liapunov Direct Method, besides error analysis, shows that a good tracking of cooperative manipulators and the manipulated object is guaranteed. Next, using MAPLE and MATLAB tools, a system of three manipulators mounted on a space free-flying robot is simulated. The task is moving an object based on given trajectories which come across an obstacle, to examine the performance of the developed control law. The results show that, even in the presence of both external disturbances and an impact due to collision with the obstacle, the response of the MIC algorithm is smooth. Moreover, based on the embedded force tracking strategy, the contact force is confined to follow a desired trajectory. Also, it is shown that decreasing the values of the controller mass matrix elements results in reducing both the object position and force tracking error.     

Dynamically stable motion planning of wheeled robots for heavy object manipulation

Heavy object manipulation by wheeled mobile manipulators (WMM) may lead to serious consequences such as postural instability, and this necessitates dynamically stable planning based on systematic analysis to better predict and eliminate the possibility of toppling down. Although the problem of stable planning has been extensively examined in the context of humanoid robotics, fewer research has been devoted to that in the field of WMMs. In the present study, this challenging issue is investigated for WMMs during heavy object manipulation tasks. It is assumed that the initial and final poses of a heavy payload are specified. Based on these known postures of the payload, two proper configurations for robotic system are defined. Then, between these two initial and final poses, appropriate trajectories for multiple robotic arms relative to the moving base are planned without considering the postural stability of the system. Next, motion of the moving base is planned so that the stability of the overall system is guaranteed while its predetermined initial and final positions and velocities are fulfilled. To this end, the problem of stable planning is solved as an optimization problem. The obtained results reveal the merits of the proposed approach.     

Performance analysis of robotic kitting systems

Robotic kitting and presenting parts in the from of a kit to an assembly robot can provide significant flexibility, control, expandability, and productivity in both the part stores and final assembly operations. The problem of selecting the proper design of a robotic kitting configuration based on desired performance criteria is discussed. Several models of recommended robotic kitting configurations were developed and then analyzed using a robot cell simulator, SINDECS-R, and a robot motion time program, RTM. Each of these models was evaluated for a variety of typical operating conditions and compared based on performance in order to provide guidance for designers. The most favorable robotic kitting design as found in this analysis is the miniload on-board robot/automated storage-retrieval kitting system.     

Dynamics of cooperating manipulators for fixtureless assembly and robust control based on fuzzy logic

This article presents the modeling of the dynamics of two cooperating robot manipulators performing assembly tasks such as the peg‐in‐hole job while coordinating the payload along the desired trajectory. The system has uncertainty due to unknown mass and moment of inertia of the manipulators and the payload, and has disturbances due to coupling forces between manipulators and due to frictional forces during the assembly process. To control the uncertain system, a robust control algorithm with computed torque control is proposed. The robust control algorithm includes fuzzy logic that has two functions: one is to regulate the magnitude of the input torque of the manipulators to not go beyond the torque saturation. The other function is to reduce trajectory tracking errors. To validate the proposed control algorithm, a numerical example using dual 3 degree‐of‐freedom manipulators is shown. ©1999 John Wiley & Sons, Inc.     

Development and evaluation of a Venus flytrap-inspired microrobot

Nature has provided the inspiration for many robots, leading to the development of biomimetic machines based on stick insects, jellyfish, butterflies, lobsters, and inchworms. Some carnivorous plants are capable of rapid motion, including mimosa, Venus flytraps, telegraph plants, sundews, and bladderworts, all of which are of interest in the design of biomimetic robots that can be activated in a controlled manner to capture prey using trigger hairs. Here, we describe a biomimetic robotic inspired by a Venus flytrap and fabricated using two ionic polymer metal composite (IPMC) actuators. First, we describe the structure of the robotic flytrap, which consists of two IPMC lobes and a proximity sensor, and discuss the design of the control circuitry. We then evaluate the deformation and bending force of the IPMC actuator with various applied signal voltages. We describe a prototype robotic flytrap utilising a proximity sensor to imitate the trigger hairs of the Venus flytrap. We conducted an experiment to assess the feasibility of the biomimetic flytrap. To evaluate grasping ability, we measured the maximum grasping payload with different applied voltages. To enlarge the working area, we integrated biomimetic walking and rotating motion into the robotic Venus flytrap. This paper describes a prototype movable robotic Venus flytrap and evaluates its walking and rotating speeds.